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An Aker BP operated oil field in the North Sea has occasionally experienced production flow instabilities in the production lines and risers. The oscillations in multiphase rates are kept within the process capacity limitation at the host installation typically by increasing backpressure (planned flaring is not allowed for on the Norwegian Continental Shelf). The heightened backpressure impacts the production potential of the field. The objective of the project described in this paper has been to develop and implement a new method for real-time production optimization providing an online assessment of slugging severity and suggested actions in order to mitigate slugging and increase production. The developed software tool has been validated using field data. A statistical approach based on the physical characteristics of the separator has been developed. A combination of transient multiphase flow simulations and data analysis has been employed in order to formulate the risk of exceeding separator constraints as a multidimensional function of the operational conditions. In order to generate a three-dimensional heat map of the risk related to the current state, operational data is continuously gathered from production sensors and transformed into pseudo-steady state values. A heat map is defined by a function where four relevant operational values can be selected. These values are: oil production rate, topside choke setting, gas lift rates and water cut. The software solution is run on a cloud infrastructure with an interactive web user interface. In a pilot program we have evaluated the ability of the stability advisor to continuously assess the severity of flow instabilities, identify measures to reduce the risk level and minimize associated production losses. The operator has identified valuable operational insights from the tool in a pilot program. The flow instabilities predicted by the model correlate well with observed data from the field. The tool is scalable to other fields with similar flow problems. Previous papers on slug flow prediction are in general conducted as offline study projects. There has been little success in making real-time scalable solutions available to continuous operations. This paper explains a method on how physical modelling of the flow system combined with statistical methods and access to real-time sensor data can provide a new approach for real-time slug flow prediction. The result demonstrates a scalable solution where output is presented in a format that can be applied by daily operations to act on and provide new and valuable production insights.
An Aker BP operated oil field in the North Sea has occasionally experienced production flow instabilities in the production lines and risers. The oscillations in multiphase rates are kept within the process capacity limitation at the host installation typically by increasing backpressure (planned flaring is not allowed for on the Norwegian Continental Shelf). The heightened backpressure impacts the production potential of the field. The objective of the project described in this paper has been to develop and implement a new method for real-time production optimization providing an online assessment of slugging severity and suggested actions in order to mitigate slugging and increase production. The developed software tool has been validated using field data. A statistical approach based on the physical characteristics of the separator has been developed. A combination of transient multiphase flow simulations and data analysis has been employed in order to formulate the risk of exceeding separator constraints as a multidimensional function of the operational conditions. In order to generate a three-dimensional heat map of the risk related to the current state, operational data is continuously gathered from production sensors and transformed into pseudo-steady state values. A heat map is defined by a function where four relevant operational values can be selected. These values are: oil production rate, topside choke setting, gas lift rates and water cut. The software solution is run on a cloud infrastructure with an interactive web user interface. In a pilot program we have evaluated the ability of the stability advisor to continuously assess the severity of flow instabilities, identify measures to reduce the risk level and minimize associated production losses. The operator has identified valuable operational insights from the tool in a pilot program. The flow instabilities predicted by the model correlate well with observed data from the field. The tool is scalable to other fields with similar flow problems. Previous papers on slug flow prediction are in general conducted as offline study projects. There has been little success in making real-time scalable solutions available to continuous operations. This paper explains a method on how physical modelling of the flow system combined with statistical methods and access to real-time sensor data can provide a new approach for real-time slug flow prediction. The result demonstrates a scalable solution where output is presented in a format that can be applied by daily operations to act on and provide new and valuable production insights.
Slugging is a dynamic flow behavior observed in many multiphase production systems. It is due to the rapid change in volumetric phase flowrates within a process. Various slug mitigation strategies have been implemented in production facilities over the world to ensure stable production and maximum field recovery. This paper aims to present the project overview, workflow and use cases for the implementation of an active slug control technology based on real-field project experiences. An active slug control algorithm can be used for slug mitigation on upstream production systems. The purpose is to stabilize production flow from the flowline inlet to the first stage separator so that stable and safe production is ensured within the system design constraints. This in turn has the potential to increase production flow and further extend field life of aging production facilities. This paper presents examples of feasibility assessments and field implementations, covering both conventional oil and gas-condensate production. An active slug control technology can be applied to both deep-water and shallow-water facilities. Installation of this slug control system requires only an update to the existing flow controller to include an additional algorithm for slug suppression at the riser top choke valve. This simple addition eliminates the requirement of active operators’ intervention in the event of slugging, as well as reducing the frequency of process trips. In comparison with other slug control methods, this technology is cost-effective since no additional process equipment is required to be installed and maintained. As a result, this significantly reduces the project execution time, avoids production disruptions, and minimizes potential HSE issues. The technology can be implemented within a year from the outset of a feasibility study. However, the technology is not appropriate for all situations due to differences in slugging nature and other subsurface issues and therefore its applicability needs to be evaluated on a case-by-case basis. With increasing number of aging offshore assets and competitiveness in the energy market, it is expected that active slug control technology will become a crucial tool to reduce production downtime and deferment. This paper also presents a workflow which aims to provide a general guideline for the feasibility assessments and implementation of this slug control technology on producing assets. The objectives of slug mitigation may vary from asset to asset due to differences in production conditions, slugging characteristics and facilities design. Therefore, strong client engagement is necessary to ensure the most optimal workflow for the technology to be implemented.
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